Remark 8 
In machine learning one uses entropic regularization rather than logarithmic barrier regularization in (REF ). The former is more efficient than the latter.
Thus, when \(d_1\)  and \(d_2\)  are large,
the entropic path \(\mathcal {C}^{T,+}_{A,b,c}\)  is preferred to the
central path \(\mathcal {C}^{R,+}_{A,b,c}\) .
We refer to [1]} for an explanation. Example REF 
and the introduction of [2]} offer details and references.

